Daniel Epstein is an Associate Professor in the Department of Informatics at the University of California, Irvine (UCI), where he leads the Personal Informatics Everyday (PIE) Lab. He holds a courtesy appointment in the Department of Computer Science and is affiliated with the Connected Learning Lab, Institute for Future Health, and Accessibility Research Collective. Epstein earned his Ph.D. in Computer Science & Engineering from the University of Washington and a B.S. in Computer Science from the University of Virginia. His research focuses on how personal tracking technology can better serve diverse users' needs, emphasizing ethical design, health equity, and long-term user engagement. Notable areas include pregnancy tracking, wearable technology for children and ADHD management, and AI-driven health chatbots. Epstein has received grants from NSF, Snap Inc., and UCI programs, totaling over $650k in funding. Epstein's work bridges HCI and health informatics, with over 60 peer-reviewed publications. He advises six Ph.D. students and has mentored numerous undergraduates. Awards include the ACM Senior Member distinction (2025), CHI Best Paper (2023), and NSF CAREER Award (2023). Professional service includes program committees for CHI, CSCW, and UbiComp, plus leadership roles in workshops like the Workgroup on Interactive Systems in Healthcare (WISH). Beyond academia, Epstein enjoys hiking, collecting turtle figures, and advocating for accessible technology.
Robin Jia is an Assistant Professor in the Thomas Lord Department of Computer Science at the University of Southern California (USC) , where he leads the AI, Language, Learning, Generalization, and Robustness (Allegro) Lab . His research focuses on enhancing the reliability and robustness of large language models (LLMs) through mechanistic understanding, benchmarking under distribution shifts, and neurosymbolic integration. Key affiliations include collaborations with the USC Keck School of Medicine and contributions to legal frameworks like the EU's Digital Services Act. Robin's research spans multiple domains, including: Scientific analysis of LLM capabilities in in-context learning , data memorization , and numerical reasoning Advancements in robust NLP systems , emphasizing uncertainty estimation and calibration Development of methods combining LLMs with symbolic solvers for complex reasoning tasks Interdisciplinary applications in medicine and law , such as privacy-preserving synthetic data generation and medical misconception evaluation . His recent publications (2024-2025) address Fourier-based numerical embeddings (NeurIPS), neurosymbolic planning (NAACL), and multimodal benchmarking (COLM), with a strong emphasis on privacy , fairness , and transparency . Scientific awards include the Google Research Scholar Award (2023) , SoCalNLP Symposium Best Paper Awards , and ACL/EMNLP outstanding papers . He advises PhD students like Johnny Wei and Ameya Godbole, and has secured grants from the NSF , USC-Capital One , and USC-Amazon .
Arti Singh is an Assistant Professor in the Department of Agronomy at Iowa State University. Her research focuses on plant breeding, soybean diseases, genomics, and phenomics, with a strong emphasis on integrating artificial intelligence and high-throughput technologies into agricultural systems. She leads projects involving AI-driven disease identification, precision agriculture, and crop improvement strategies. Her expertise includes developing machine learning models for real-time weed and insect classification (e.g., WeedNet and InsectNet), deploying drones and ground robots for crop phenotyping, and leveraging genomic data to map traits like flowering time and disease resistance in legumes. Singh collaborates on initiatives like the AIIRA Institute for Resilient Agriculture and the BioTrove biodiversity dataset. Singh’s work spans plant stress phenotyping, digital twin technologies for plant sciences, and multi-sensor phenotyping for early disease detection. Her research bridges computational methods with traditional agronomy, aiming to enhance crop resilience and sustainability in the face of environmental challenges. Her recent projects include optimizing robotic navigation for precision agriculture, improving soybean yield estimation via video analysis, and dissecting genetic architectures of traits in mungbean and soybean using GWAS and genomic tools. She actively contributes to conferences and publishes in high-impact journals, advancing both foundational and applied aspects of agricultural science.
Tanzeem Choudhury is a Professor at the Jacobs Technion-Cornell Institute at Cornell Tech, specializing in Information Sciences. She co-founded HealthRhythms Inc. and directs the People-Aware Computing lab, focusing on machine learning for human activity and social network analysis. Her work pioneered the 'Reality Mining' field, leveraging mobile sensors to model social interactions. Choudhury holds a Ph.D. from MIT's Media Lab and B.S. in Electrical Engineering from the University of Rochester. Her research spans wearable tech, mental health interventions, and ubiquitous computing. Notable projects include affective touch wearables for anxiety reduction, stress detection systems (e.g., StressSense), and the BeWell app for well-being monitoring. Choudhury has been recognized as an ACM Fellow and SIGCHI Academy member, with impactful contributions to healthcare technology and sensor-based behavioral analysis. Current lab initiatives include developing closed-loop interventions for mental health, equity-driven sensing systems, and exploring AI integration in psychotherapy. She advises PhD students on topics like digital biomarkers, burnout detection in healthcare workers, and smartphone-based mental health assessment. Education: Ph.D. in Media Arts & Sciences (MIT), M.S. (MIT Media Lab), B.S. in Electrical Engineering (University of Rochester) Lab Team: Includes PhD candidates (Dan Adler, Yiran Zhao) and researchers focusing on health AI, wearable devices, and clinical applications. Major Awards: ACM Fellowship (2020), SIGCHI Academy (2018), Best Paper Awards at Ubicomp and MobileHCI conferences. Key Projects: OptoBeat (skin-tone calibrated blood oxygen sensor), EmotionCheck (anxiety intervention), and Affective Touch devices.
Sean Cao serves as Associate Professor (with tenure) at the Robert H. Smith School of Business, University of Maryland, where he is Director and Co-founder of the AI Initiative for Capital Market Research. He also holds an affiliation as professor at Harvard Business School's D 3 Institute. His academic journey began with a Ph.D. from the University of Illinois at Urbana-Champaign. Dr. Cao's research focuses on the intersection of artificial intelligence and capital markets, with particular expertise in how machine learning transforms financial analysis, corporate disclosure practices, and investment decision-making. His work examines the evolving relationship between human analysts and AI systems, blockchain applications in financial reporting, and the strategic adaptation of corporate communications for machine readership. He has pioneered research on the "AI divide" among investor groups and developed frameworks for human-AI collaborative stock analysis. His publication portfolio spans top journals including Journal of Financial Economics, Review of Financial Studies, Journal of Accounting Research, and Management Science. The research demonstrates consistent thematic progression toward increasingly sophisticated AI applications in finance, with recent work exploring distributed ledger technologies for auditing, machine learning for extracting private information from disclosures, and the economics of greenwashing in ESG funds. His studies frequently combine textual analysis with traditional financial metrics to uncover novel market insights. Fama-DFA Prize from Journal of Financial Economics for best paper in capital markets and asset pricing Michael J. Brennan Award from Review of Financial Studies Deloitte Initiative for AI and Learning award for developing trustworthy AI for social equity PanAgora Asset Management's Dr. Richard A. Crowell Memorial Prize Multiple best paper awards from Midwest Finance Association, Global AI Finance Conference, and Asian Finance Association Dr. Cao has delivered over 200 invited research talks at major institutions including the Central Bank of Japan, Central Bank of Thailand, and U.S. Securities and Exchange Commission. He serves as Guest Associate Editor for Management Science and has co-chaired Review of Financial Studies conferences on FinTech and Machine Learning. His educational initiatives include a widely adopted free AI textbook for finance and accounting that has been implemented at universities worldwide including Indiana University, UT Dallas, and University of Minnesota. As Director of the AI Initiative for Capital Market Research, Dr. Cao leads a multidisciplinary team exploring practical AI applications in finance. The initiative has secured significant funding including a $150,000 grant from GRF CPAs & Advisors. His research group maintains strong industry connections through partnerships with regulatory bodies, financial institutions, and technology companies, facilitating the translation of academic research into practical financial applications.
Dr. Kaya de Barbaro is an Associate Professor in the Department of Psychology at the University of Texas at Austin (College of Liberal Arts). She holds a Ph.D. from the University of California San Diego. Her research focuses on bridging computer science and developmental/clinical psychology, particularly maternal mental health and infant social-emotional development. She directs the Daily Activity Lab, which uses mobile/wearable sensors and machine learning to analyze real-world interactions, aiming to develop just-in-time interventions for new mothers. Key research areas include maternal-infant dynamics, physiological synchronization, and the impact of environmental chaos on development. She has pioneered methods for analyzing high-density data, such as Granger causality and machine learning algorithms to detect behaviors like crying and holding. Recent work emphasizes leveraging ecological momentary assessment surveys and 24-hour LENA audio recordings to understand proximal mechanisms of development. Dr. de Barbaro teaches Psychology 333D (Introduction to Developmental Psychology) and has developed curricula for both in-person and online formats. She is actively involved in training students through the Eureka program at UT Austin. Her lab collaborates on tools like chatbots for postpartum mental health and has published extensively on sensor-based methodologies in developmental science.
Bobak Mortazavi is an Associate Professor in the Department of Computer Science & Engineering at Texas A&M University. His research focuses on medical analytics, machine learning, wearable sensors, and cyber-physical systems. He leads interdisciplinary projects in healthcare technology, including AI-driven diagnostics and predictive modeling for cardiovascular diseases. He has received notable awards such as the Best Demonstration Award at IEEE EMBS 2012 and the Best Paper Award at the Fourth International Conference on Data Analytics 2015. His work bridges machine learning with clinical applications, emphasizing practical solutions for healthcare challenges. Recent research includes developing AI tools for aortic stenosis detection, electrolyte estimation via ECG, and real-time patient monitoring systems. He collaborates with industry and academic partners to advance telemedicine and wearable health technologies. Key contributions include the SMART-LV project for smartphone-based cardiac diagnostics and the ArterialNet framework for blood pressure reconstruction using wearable sensors. His work is published in top journals like IEEE Journal of Biomedical and Health Informatics and Elsevier's Pervasive and Mobile Computing.
David Mazières is a Professor at Stanford University , affiliated with the School of Engineering and the Department of Computer Science . He serves as a software engineer at the Stellar Development Foundation . His work bridges academic research and industry applications in distributed systems and security. University: Stanford University Academic Rank: Professor Email: dm@scs.stanford.edu Research Interests: David Mazières' research focuses on distributed systems , cryptocurrencies , and computer security . Key areas include consensus protocols (e.g., Stellar ), low-latency scheduling ( Syrup , Shinjuku ), and cryptographic techniques for privacy and security ( SafetyPin , CCFI ). Key Achievements: His notable works include: TCP-ENO (RFC 8547) for secure transport protocols Stellar Consensus Protocol for decentralized finance SOSP 1999 Best Paper for 'Separating key management from file system security' Teaching Contributions: He has taught core and advanced courses at Stanford since 2005, including CS212 (Operating Systems) , CS240h (Functional Systems in Haskell) , and CS251 (Cryptocurrencies and Blockchain Technologies) . Previously taught courses at NYU (2001-2005).
Dr. Laura Channing serves as Assistant Professor in Economic History within the Department of History at Durham University, concurrently holding roles as Department Representative and Fellow of the Durham Research Methods Centre. Her academic foundation includes a History degree from King's College London, followed by an MPhil in Economic and Social History (2017) and PhD in History (2021) from the University of Cambridge. Distinguished appointments include the Jane Eliza Procter Fellowship at Princeton University (2019-2020), Economic History Society Anniversary Fellowship at the Institute of Historical Research, and Visiting Fellowship at LSE's Department of Economic History. Channing's research pioneers interdisciplinary analysis of West African economic development from the 19th-20th centuries, specializing in colonial taxation systems, labor dynamics, and living standards. Her methodological innovation integrates qualitative archives with newly digitized quantitative sources from British and African repositories, currently culminating in a monograph on taxation-representation relationships in West African colonies. Recent publications reveal consistent focus on fiscal governance within composite colonial states and African agency in humanitarian frameworks. Jane Eliza Procter Fellow at Princeton University Economic History Society Anniversary Fellow at the Institute of Historical Research Her teaching expertise in African and Economic History, demonstrated during LSE appointments, complements active contributions to the Durham Research Methods Centre's interdisciplinary initiatives in historical methodology and data analysis.
Erik Ketzan is a Lecturer in Digital Humanities and Cultural Computation at King's College London. He holds a PhD in English/Digital Humanities from Birkbeck, University of London, and has held postdoctoral roles at the University of Cologne and Trinity College Dublin, where he coordinated the MA in Digital Humanities and Culture. His research focuses on computational literary studies, legal/ethical issues in digital research, and corpus stylistics. He has published widely on topics such as Thomas Pynchon’s computational stylistics, legal frameworks for digital humanities research, and gender bias in historical texts. His work includes developing tools like Coleto for textual variant analysis and co-authoring the book *Thomas Pynchon and the Digital Humanities* (2022). Ketzan actively engages in policy advocacy, advising on copyright and data protection in DH, and has contributed to projects like CLARIN and the Leibniz Institute for the German Language. Education: PhD in English/Digital Humanities, Birkbeck, University of London Postdoctoral Researcher, University of Cologne (EncycNet Project) Postdoctoral Research and Teaching Fellow, Trinity College Dublin Research Interests: Computational approaches to literary analysis, legal challenges in data-driven research, corpus stylistics, and gender studies in historical corpora. Teaching: Courses include Python for the humanities, computational literary studies, and legal issues in digital humanities.
Olga Sorkine-Hornung is a Professor of Computer Science at ETH Zurich and head of the Institute of Visual Computing. She leads the Interactive Geometry Lab, focusing on theoretical and practical advancements in digital content creation, geometry processing, and shape modeling. Current position: ETH Zurich, Department of Computer Science Previous roles: Courant Institute (NYU), Technical University of Berlin Education: BSc and PhD from Tel Aviv University, postdoc at TU Berlin Her research spans shape representation, digital fabrication, computer animation, and fundamental geometry processing. Key contributions include Laplacian surface editing, as-rigid-as-possible deformation, and generalized winding numbers. She works on applications in VR, AR, and autonomous systems. Awards include Test of Time Awards (2024), ACM Fellow (2020), ERC Consolidator Grant (2020), and EUROGRAPHICS Young Researcher Award (2008). She has supervised numerous students and co-developed software libraries like libigl and Instant Meshes . Co-chair roles for SIGGRAPH, Eurographics, and Pacific Graphics Editorial board member for ACM Transactions on Graphics and other journals Keynote speaker at VMV, CVPR, and SIAM conferences Her work bridges mathematical rigor with practical implementation, advancing computer graphics and geometry processing through intuitive algorithms that maintain surface detail while enabling efficient computation.
Alane Suhr is an Assistant Professor at UC Berkeley's Electrical Engineering and Computer Sciences (EECS) department and a member of the Berkeley Artificial Intelligence Research Lab (BAIR). Her research focuses on natural language processing (NLP), machine learning, and computer vision, emphasizing systems that interact with humans through language. She designs models and datasets for language grounding (e.g., NLVR) and develops algorithms for learning through interaction. Education: PhD in Computer Science, Cornell University (2022), advised by Yoav Artzi Bachelor's in Computer Science and Engineering, Ohio State University (2016), with a Linguistics minor Research Interests: Interactive systems for collaborative language use (e.g., CerealBar) Language grounding in multimodal contexts Embodied agents and reinforcement learning Generalization in NLP and the role of language in learning Key Contributions: Developed the NLVR dataset for visual reasoning with natural language Pioneered work on SWE-Gym for training software engineering agents Contributed to research on language models' sensitivity and commonsense reasoning Awards: ACM Doctoral Dissertation Award (2022) Outstanding Paper Awards at ACL 2023 and EMNLP 2021 Professional Activities: Organized workshops at ICML, NeurIPS, and ACL on topics like agents, generalization, and theory of mind Active in academic outreach and conference speaking (e.g., ICML, NeurIPS, CVPR) Labs/Teams: Berkeley Artificial Intelligence Research (BAIR) Lab SWE-Gym research group
Lutz Schubert is a researcher at the Institute of Computer Science , University of Cologne. He focuses on efficient distributed and parallel execution environments for heterogeneous systems, notably the MyThOS operating system in collaboration with Brandenburg University of Technology, Cottbus-Senftenberg. His interdisciplinary work bridges computer science and digital archaeology , addressing modeling of non-deterministic events from sparse excavation data and exploring human behavior constraints in archaeological contexts. Research Interests Design of modular, scalable operating systems for distributed systems Optimization of execution environments for heterogeneous hardware Application of complex systems modeling to digital archaeology Statistical and probabilistic methods for archaeological interpretation Autonomic resource distribution and adaptation in computing Publication Trends : His work spans operating systems , parallel computing , and digital humanities , with recent emphasis on probabilistic reasoning in archaeology and adaptive OS design for multicore architectures. Labs & Collaborations : He collaborates with Brandenburg University of Technology on MyThOS and leads research in computational archaeology as chair of Computer Applications and Quantitative Methods in Archaeology (CAA) , Germany.
Maile Arvin is a Kanaka Maoli feminist scholar and Assistant Professor at the Department of Ethnic Studies, University of Hawaiʻi at Mānoa. Her research and teaching focus on Indigenous relationships to land, histories of race and settler colonialism in Hawaiʻi, Oceania, and the United States. Previously, she was faculty in History and Gender Studies at the University of Utah and founding director of the Center for Pasifika Indigenous Knowledges. PhD in Ethnic Studies, University of California San Diego (2013) MA in Ethnic Studies, University of California San Diego (2009) BA in English, Swarthmore College (2005) Her research examines: Colonial production of racial categories, particularly Polynesians as an 'almost white race' in historical social science History of incarceration of Native Hawaiian children in government institutions (1865–1960s) Intersection of settler colonialism and Indigenous feminisms Critique of eugenics and genomic studies in the Pacific Community-engaged memorialization projects in Hawaiʻi Recent scholarly trends include analyses of Indigenous sovereignty, critiques of settler colonial whiteness, and interdisciplinary studies of race-gender dynamics. Arvin's publications explore Polynesian racialization, decolonial feminism, and the socioeconomic impacts of colonial institutions. NEH Chair's Grant for Nā Lei Poina ʻOle ACLS Digital Justice Seed Grant Arvin leads Nā Lei Poina ʻOle (Beloved Children Never Forgotten), a community history project about reformatories and industrial schools in Hawaiʻi. In collaboration with Kawela Farrant and the North Shore Community Land Trust, this project uses archival and oral histories to confront the legacy of child incarceration. She also critiques the nonprofit-industrial complex's role in limiting Indigenous sovereignty.
Shreyas Sen is the Elmore Associate Professor of Electrical and Computer Engineering at Purdue University, jointly affiliated with the School of Biomedical Engineering. He directs the Center for Internet of Bodies (C-IoB) and leads the SPARC Lab, focusing on circuits/systems for secure, energy-efficient body-centric communication and biomedical applications. Education: B.E. (Jadavpur University, 2006), M.S. & Ph.D. (Georgia Tech, 2009-2011). His research spans Human Body Communication (HBC), hardware security, IoT/IoB systems, and low-power sensing. Notable innovations include Electro-Quasistatic HBC (EQS-HBC) technology, which enables covert body-wire communication with 100x lower energy than conventional methods. Research Themes: Secure communication for medical wearables Physical layer security in IoT Ultra-low-power biosensors Side-channel attack mitigation in cryptographic ICs Publications: Over 200 papers in top venues (ISSCC, DAC, CICC, HOST) with focus on HBC systems, electromagnetic security, and biomedical circuits. Recent work explores EQS-HBC privacy properties (Nature Scientific Reports, 2019) and 350x current-domain signature attenuation for AES security (ISSCC 2020). Awards: NSF CAREER Award (2020) AFOSR Young Investigator (2016) MIT TR35 India (2018) 9 Best Paper Awards Intel Outstanding Researcher (2020) He advises over 20 students and leads industry collaborations through Ixana Inc. (founded 2020), commercializing EQS-HBC technology. Current efforts include EQS-based authentication systems and radiation dosimetry wearables.
